Healthcare, as a basic human right, has often become the focus of the development of innovative technologies. Technological progress has significantly contributed to the provision of high-quality, on-time, acceptable, and affordable healthcare. Advancements in nanoscience have led to the emergence of a new generation of nanostructures. Each of them has a unique set of properties that account for their astonishing applications. Since its inception, nanotechnology has continuously affected healthcare and has exerted a tremendous influence on its transformation, contributing to better outcomes. In the last two decades, the world has seen nanotechnology taking steps towards its omnipresence and the process has been accelerated by extensive research in various healthcare sectors. The inclusion of nanotechnology and its allied nanocarriers/nanosystems in medicine is known as nanomedicine, a field that has brought about numerous benefits in disease prevention, diagnosis, and treatment. Various nanosystems have been found to be better candidates for theranostic purposes, in contrast to conventional ones. This review paper will shed light on medically significant nanosystems, as well as their applications and limitations in areas such as gene therapy, targeted drug delivery, and in the treatment of cancer and various genetic diseases. Although nanotechnology holds immense potential, it is yet to be exploited. More efforts need to be directed to overcome these limitations and make full use of its potential in order to revolutionize the healthcare sector in near future.

Population-level serologic testing has demonstrated groundbreaking results in monitoring the prevalence and case-fatality of COVID-19 within a population. In Pakistan, Getz Pharma conducted a sero-prevalence survey on a sample of 24,210 individuals using the IgG/IgM Test Kit (Colloidal gold) with follow-up and sequential testing after every 15-20 days on a sub-sample. This is the first of its kind, large scale census conducted on a dense, urban, working population in Pakistan. The study results reveal that from 24,210 individuals screened, 17.5% tested positive, with 7% IgM positive, 6.0% IgG positive and 4.5% combined IgM and IgG positive. These findings have been extrapolated to the rest of the urban, adult, working population of Pakistan, and as of 6th July, 2020, 4.11 million people in Pakistan have been infected with COVID-19, which is 17.7 times higher than the current number of 231,818 symptom-based PCR cases reported by the government which exclude asymptomatic cases.

MetS is a condition characterized by chronic low-grade inflammation, which arises because of increased abdominal adiposity and IR. Large multicenter studies are needed to gain insight into its pathogenesis and derive treatment strategies.

High end-to-end delay is a major challenge in autonomous underwater vehicle (AUV)-aided routing protocols for underwater monitoring applications. In this paper, a new routing protocol called atomic-shaped efficient delay and data gathering (ASEDG) has been introduced for underwater wireless sensor networks. The ASEDG is divided into two phases; in the first phase, the atomic-shaped trajectory model with horizontal and vertical ellipticals was designed for the movement of the AUV. In the second phase, two types of delay models were considered to make our protocol more delay efficient: member nodes (MNs) to MNs and MNs to gateway nodes (GNs). The MNs-to-MNs delay in the network specifies how long is required for the selection of the next possible forwarders by eliminating the chances of backtracking and a higher number of association links. The MNs-to-GNs delay is considered to choose the path from a multipath environment that takes a minimum amount of time for sending the packet from its generation to destination node. For efficient data gathering, this new trajectory model creates the maximum possible GNs for the association of the MNs. Furthermore, our protocol, ASEDG, has been evaluated by using the aquasim network simulator (NS-2), and its results were compared with the already existing protocol, an efficient data gathering (AEDG) routing protocol. The simulation results show that the ASEDG performed better than the AEDG in terms of end-to-end delay and throughput.

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